Classification and Learning Using Genetic Algorithms
Applications in Bioinformatics and Web Intelligence
1st Edition
Published on 17. May 2007
XVI, 311 pages
978-3-540-49607-6 (ISBN)
Description
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It provides a balanced mixture of theories, algorithms and applications, and in particular results from the bioinformatics and Web intelligence domains. The book will be useful to graduate students and researchers in computer science, electrical engineering, systems science, and information technology, both as a text and reference book. Researchers and practitioners in industry working in system design, control, pattern recognition, data mining, soft computing, bioinformatics and Web intelligence will also benefit.
Reviews / Votes
"This book tries to balance the mixture of theories, algorithms, and applications and is a good reference for people who want to solve a complex optimization problem for their field. ... Overall, this book is well organized and well written. There is no doubt that this is another good pattern recognition reference to have on one's bookshelf." (Zheng Liu, IAPR Newsletter 30(4), October 2008)More details
Other editions
Additional editions
Sanghamitra Bandyopadhyay | Sankar Kumar Pal
Classification and Learning Using Genetic Algorithms
Applications in Bioinformatics and Web Intelligence
Book
04/2007
Springer
€106.99
Shipment within 10-15 days
Content
Genetic Algorithms.- Supervised Classification Using Genetic Algorithms.- Theoretical Analysis of the GA-classifier.- Variable String Lengths in GA-classifier.- Chromosome Differentiation in VGA-classifier.- Multiobjective VGA-classifier and Quantitative Indices.- Genetic Algorithms in Clustering.- Genetic Learning in Bioinformatics.- Genetic Algorithms and Web Intelligence.
